# PGVector

This page covers how to use the Postgres [PGVector](https://github.com/pgvector/pgvector) ecosystem within LangChain
It is broken into two parts: installation and setup, and then references to specific PGVector wrappers.

## Installation
- Install the Python package with `pip install pgvector`


## Setup
1. The first step is to create a database with the `pgvector` extension installed.

    Follow the steps at [PGVector Installation Steps](https://github.com/pgvector/pgvector#installation) to install the database and the extension. The docker image is the easiest way to get started.

## Wrappers

### VectorStore

There exists a wrapper around Postgres vector databases, allowing you to use it as a vectorstore,
whether for semantic search or example selection.

To import this vectorstore:
```python
from langchain.vectorstores.pgvector import PGVector
```

### Usage

For a more detailed walkthrough of the PGVector Wrapper, see [this notebook](/docs/modules/data_connection/vectorstores/integrations/pgvector.html)
